Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses.

Stress Knowledge Map (SKM, https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs describing current knowledge of biochemical, signalling, and regulatory molecular interactions in plants: a highly curated model of plant stress signalling (PSS, 543 reactions) and a large comprehensive knowledge network (CKN, 488,390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entrypoint for plant stress response investigations and the related growth trade-offs as well as interactive exploration of current knowledge. PSS is also formulated as qualitative and quantitative models for systems biology, and thus represents a starting point of a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation, design of validation experiments, or to gain new insights into experimental observations in plant biology.

Transcriptional and epigenetic changes during tomato yellow leaf curl virus infection in tomato.

BACKGROUND: Geminiviruses are DNA plant viruses that cause highly damaging diseases affecting crops worldwide. During the infection, geminiviruses hijack cellular processes, suppress plant defenses, and cause a massive reprogramming of the infected cells leading to major changes in the whole plant homeostasis. The advances in sequencing technologies allow the simultaneous analysis of multiple aspects of viral infection at a large scale, generating new insights into the molecular mechanisms underlying plant-virus interactions. However, an integrative study of the changes in the host transcriptome, small RNA profile and methylome during a geminivirus infection has not been performed yet. Using a time-scale approach, we aim to decipher the gene regulation in tomato in response to the infection with the geminivirus, tomato yellow leaf curl virus (TYLCV). RESULTS: We showed that tomato undergoes substantial transcriptional and post-transcriptional changes upon TYLCV infection and identified the main altered regulatory pathways. Interestingly, although the principal plant defense-related processes, gene silencing and the immune response were induced, this cannot prevent the establishment of the infection. Moreover, we identified extra- and intracellular immune receptors as targets for the deregulated microRNAs (miRNAs) and established a network for those that also produced phased secondary small interfering RNAs (phasiRNAs). On the other hand, there were no significant genome-wide changes in tomato methylome at 14 days post infection, the time point at which the symptoms were general, and the amount of viral DNA had reached its maximum level, but we were able to identify differentially methylated regions that could be involved in the transcriptional regulation of some of the differentially expressed genes. CONCLUSION: We have conducted a comprehensive and reliable study on the changes at transcriptional, post-transcriptional and epigenetic levels in tomato throughout TYLCV infection. The generated genomic information is substantial for understanding the genetic, molecular and physiological changes caused by TYLCV infection in tomato.

Candidate pathogenicity factor/effector proteins of 'Candidatus Phytoplasma solani' modulate plant carbohydrate metabolism, accelerate the ascorbate-glutathione cycle, and induce autophagosomes.

The pathogenicity of intracellular plant pathogenic bacteria is associated with the action of pathogenicity factors/effectors, but their physiological roles for most phytoplasma species, including 'Candidiatus Phytoplasma solani' are unknown. Six putative pathogenicity factors/effectors from six different strains of 'Ca. P. solani' were selected by bioinformatic analysis. The way in which they manipulate the host cellular machinery was elucidated by analyzing Nicotiana benthamiana leaves after Agrobacterium-mediated transient transformation with the pathogenicity factor/effector constructs using confocal microscopy, pull-down, and co-immunoprecipitation, and enzyme assays. Candidate pathogenicity factors/effectors were shown to modulate plant carbohydrate metabolism and the ascorbate-glutathione cycle and to induce autophagosomes. PoStoSP06, PoStoSP13, and PoStoSP28 were localized in the nucleus and cytosol. The most active effector in the processes studied was PoStoSP06. PoStoSP18 was associated with an increase in phosphoglucomutase activity, whereas PoStoSP28, previously annotated as an antigenic membrane protein StAMP, specifically interacted with phosphoglucomutase. PoStoSP04 induced only the ascorbate-glutathione cycle along with other pathogenicity factors/effectors. Candidate pathogenicity factors/effectors were involved in reprogramming host carbohydrate metabolism in favor of phytoplasma own growth and infection. They were specifically associated with three distinct metabolic pathways leading to fructose-6-phosphate as an input substrate for glycolysis. The possible significance of autophagosome induction by PoStoSP28 is discussed.

pISA-tree - a data management framework for life science research projects using a standardised directory tree.

We developed pISA-tree, a straightforward and flexible data management solution for organisation of life science project-associated research data and metadata. pISA-tree was initiated by end-user requirements thus its strong points are practicality and low maintenance cost. It enables on-the-fly creation of enriched directory tree structure (project/Investigation/Study/Assay) based on the ISA model, in a standardised manner via consecutive batch files. Templates-based metadata is generated in parallel at each level enabling guided submission of experiment metadata. pISA-tree is complemented by two R packages, pisar and seekr. pisar facilitates integration of pISA-tree datasets into bioinformatic pipelines and generation of ISA-Tab exports. seekr enables synchronisation with the FAIRDOMHub repository. Applicability of pISA-tree was demonstrated in several national and international multi-partner projects. The system thus supports findable, accessible, interoperable and reusable (FAIR) research and is in accordance with the Open Science initiative. Source code and documentation of pISA-tree are available at https://github.com/NIB-SI/pISA-tree .

Fermentative Indole Production via Bacterial Tryptophan Synthase Alpha Subunit and Plant Indole-3-Glycerol Phosphate Lyase Enzymes.

Indole is produced in nature by diverse organisms and exhibits a characteristic odor described as animal, fecal, and floral. In addition, it contributes to the flavor in foods, and it is applied in the fragrance and flavor industry. In nature, indole is synthesized either from tryptophan by bacterial tryptophanases (TNAs) or from indole-3-glycerol phosphate (IGP) by plant indole-3-glycerol phosphate lyases (IGLs). While it is widely accepted that the tryptophan synthase α-subunit (TSA) has intrinsically low IGL activity in the absence of the tryptophan synthase ß-subunit, in this study, we show that Corynebacterium glutamicum TSA functions as a bona fide IGL and can support fermentative indole production in strains providing IGP. By bioprospecting additional bacterial TSAs and plant IGLs that function as bona fide IGLs were identified. Capturing indole in an overlay enabled indole production to titers of about 0.7 g L-1 in fermentations using C. glutamicum strains expressing either the endogenous TSA gene or the IGL gene from wheat.

A Comprehensive Guide to Potato Transcriptome Assembly.

We have witnessed a rapid advancement in high-throughput genome sequencing and the maturation of long-read technologies. However, an accurate assembly of polyploid potato genomes still remains challenging. Sequencing the double-monoploid genome of Solanum tuberosum Group Phureja (Xu et al., Nature 475:189-195, 2011) has enabled functional studies of polyploid potato cultivars using RNA sequencing (RNA-Seq) technologies, although with the limitation of not covering cultivar-specific gene expression. The accumulated RNA-Seq datasets from these cultivars can be leveraged to assemble tetraploid potato transcriptomes that enable the analysis of genes that are not limited to reference genome annotations. To increase transcriptomes' quality, short-read assemblies are nowadays complemented with full-length transcriptome sequencing using Pacific Biosciences or Oxford Nanopore platforms. In this chapter we give a detailed guide on a pipeline for de novo transcriptome assembly of polyploid potato genotypes and their integration into a pan-transcriptome.

Methodologies for Discovery and Quantitative Profiling of sRNAs in Potato.

Small RNAs (sRNAs) are short noncoding RNAs involved in the regulation of a wide range of biological processes in plants. Advances in high-throughput sequencing and development of new computational tools had facilitated the discovery of different classes of sRNAs, their quantification, and elucidation of their functional role in gene expression regulation by target transcript predictions. The workflow presented here allows identification of different sRNA species: known and novel potato miRNAs, and their sequence variants (isomiRs), as well as identification of phased small interfering RNAs (phasiRNAs). Moreover, it includes steps for differential expression analysis to search for regulated sRNAs across different tested biological conditions. In addition, it describes two different methods for predicting sRNA targets, in silico prediction, and degradome sequencing data analysis. All steps of the workflow are written in a clear and user-friendly way; thus they can be followed also by the users with minimal bioinformatics knowledge. We also included several in-house scripts together with valuable notes to facilitate data (pre)processing steps and to reduce the analysis time.

Prunus persica plant endogenous peptides PpPep1 and PpPep2 cause PTI-like transcriptome reprogramming in peach and enhance resistance to Xanthomonas arboricola pv. pruni.

BACKGROUND: Rosaceae species are economically highly relevant crops. Their cultivation systems are constrained by phytopathogens causing severe losses. Plants respond to invading pathogens through signaling mechanisms, a component of which are of them being plant elicitor peptides (Peps). Exogenous application of Peps activates defense mechanisms and reduces the symptoms of pathogen infection in various pathosystems. We have previously identified the Rosaceae Peps and showed, in an ex vivo system, that their topical application efficiently enhanced resistance to the bacterial pathogen Xanthomonas arboricola pv. pruni (Xap). RESULTS: Here we demonstrate the effectiveness of Prunus persica peptides PpPep1 and PpPep2 in protecting peach plants in vivo at nanomolar doses, with 40% reduction of the symptoms following Xap massive infection. We used deep sequencing to characterize the transcriptomic response of peach plants to preventive treatment with PpPep1 and PpPep2. The two peptides induced highly similar massive transcriptomic reprogramming in the plant. One hour, 1 day and 2 days after peptide application there were changes in expression in up to 8% of peach genes. We visualized the transcriptomics dynamics in a background knowledge network and detected the minor variations between plant responses to PpPep1 and PpPep2, which might explain their slightly different protective effects. By designing a P. persica Pep background knowledge network, comparison of our data and previously published immune response datasets was possible. CONCLUSIONS: Topical application of P. persica Peps mimics the PTI natural response and protects plants against massive Xap infection. This makes them good candidates for deployment of natural, targeted and environmental-friendly strategies to enhance resistance in Prunus species and prevent important biotic diseases.

Precision transcriptomics of viral foci reveals the spatial regulation of immune-signaling genes and identifies RBOHD as an important player in the incompatible interaction between potato virus Y and potato.

Whereas the activation of resistance (R) proteins has been intensively studied, the downstream signaling mechanisms leading to the restriction of the pathogen remain mostly unknown. We studied the immunity network response conditioned by the potato Ny-1 gene against potato virus Y. We analyzed the processes in the cell death zone and surrounding tissue on the biochemical and gene expression levels in order to reveal the spatiotemporal regulation of the immune response. We show that the transcriptional response in the cell death zone and surrounding tissue is dependent on salicylic acid (SA). For some genes the spatiotemporal regulation is completely lost in the SA-deficient line, whereas other genes show a different response, indicating multiple connections between hormonal signaling modules. The induction of NADPH oxidase RBOHD expression occurs specifically on the lesion border during the resistance response. In plants with silenced RBOHD, the functionality of the resistance response is perturbed and the spread of the virus is not arrested at the site of infection. RBOHD is required for the spatial accumulation of SA, and conversely RBOHD is under the transcriptional regulation of SA. Using spatially resolved RNA-seq, we also identified spatial regulation of an UDP-glucosyltransferase, another component in feedback activation of SA biosynthesis, thus deciphering a novel aspect of resistance signaling.

Cultivar-specific transcriptome and pan-transcriptome reconstruction of tetraploid potato.

Although the reference genome of Solanum tuberosum Group Phureja double-monoploid (DM) clone is available, knowledge on the genetic diversity of the highly heterozygous tetraploid Group Tuberosum, representing most cultivated varieties, remains largely unexplored. This lack of knowledge hinders further progress in potato research. In conducted investigation, we first merged and manually curated the two existing partially-overlapping DM genome-based gene models, creating a union of genes in Phureja scaffold. Next, we compiled available and newly generated RNA-Seq datasets (cca. 1.5 billion reads) for three tetraploid potato genotypes (cultivar Désirée, cultivar Rywal, and breeding clone PW363) with diverse breeding pedigrees. Short-read transcriptomes were assembled using several de novo assemblers under different settings to test for optimal outcome. For cultivar Rywal, PacBio Iso-Seq full-length transcriptome sequencing was also performed. EvidentialGene redundancy-reducing pipeline complemented with in-house developed scripts was employed to produce accurate and complete cultivar-specific transcriptomes, as well as to attain the pan-transcriptome. The generated transcriptomes and pan-transcriptome represent a valuable resource for potato gene variability exploration, high-throughput omics analyses, and breeding programmes.

IGLOSS: iterative gapless local similarity search.

SUMMARY: Searching for local sequence patterns is one of the basic tasks in bioinformatics. Sequence patterns might have structural, functional or some other relevance, and numerous methods have been developed to detect and analyze them. These methods often depend on the wealth of information already collected. The explosion in the number of newly available sequences calls for novel methods to explore local sequence similarity. We have developed a new method for iterative motif scanning that will look for ungapped sequence patterns similar to a submitted query. Using careful parameter estimation and an adaptation of a fast string-matching algorithm, the method performs significantly better in this context than the existing software. AVAILABILITY AND IMPLEMENTATION: The IGLOSS web server is available at http://compbioserv.math.hr/igloss/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DiNAR: revealing hidden patterns of plant signalling dynamics using Differential Network Analysis in R.

BACKGROUND: Progress in high-throughput molecular methods accompanied by more complex experimental designs demands novel data visualisation solutions. To specifically answer the question which parts of the specifical biological system are responding in particular perturbation, integrative approach in which experimental data are superimposed on a prior knowledge network is shown to be advantageous. RESULTS: We have developed DiNAR, Differential Network Analysis in R, a user-friendly application with dynamic visualisation that integrates multiple condition high-throughput data and extensive biological prior knowledge. Implemented differential network approach and embedded network analysis allow users to analyse condition-specific responses in the context of topology of interest (e.g. immune signalling network) and extract knowledge concerning patterns of signalling dynamics (i.e. rewiring in network structure between two or more biological conditions). We validated the usability of software on the Arabidopsis thaliana and Solanum tuberosum datasets, but it is set to handle any biological instances. CONCLUSIONS: DiNAR facilitates detection of network-rewiring events, gene prioritisation for future experimental design and allows capturing dynamics of complex biological system. The fully cross-platform Shiny App is hosted and freely available at https://nib-si.shinyapps.io/DiNAR. The most recent version of the source code is available at https://github.com/NIB-SI/DiNAR/ with a DOI 10.5281/zenodo.1230523 of the archived version in Zenodo.

Cell Death Is Not Sufficient for the Restriction of Potato Virus Y Spread in Hypersensitive Response-Conferred Resistance in Potato.

Hypersensitive response (HR)-conferred resistance to viral infection restricts the virus spread and is accompanied by the induction of cell death, manifested as the formation of necrotic lesions. While it is known that salicylic acid is the key component in the orchestration of the events restricting viral spread in HR, the exact function of the cell death in resistance is still unknown. We show that potato virus Y (PVY) can be detected outside the cell death zone in Ny-1-mediated HR in potato plants (cv. Rywal), observed as individual infected cells or small clusters of infected cells outside the cell death zone. By exploiting the features of temperature dependent Ny-1-mediated resistance, we confirmed that the cells at the border of the cell death zone are alive and harbor viable PVY that is able to reinitiate infection. To get additional insights into this phenomenon we further studied the dynamics of both cell death zone expansion and occurrence of viral infected cell islands outside it. We compared the response of Rywal plants to their transgenic counterparts, impaired in SA accumulation (NahG-Rywal), where the lesions occur but the spread of the virus is not restricted. We show that the virus is detected outside the cell death zone in all lesion developmental stages of HR lesions. We also measured the dynamics of lesions expansion in both genotypes. We show that while rapid lesion expansion is observed in SA-depleted plants, virus spread is even faster. On the other hand the majority of analyzed lesions slowly expand also in HR-conferred resistance opening the possibility that the infected cells are eventually engulfed by cell death zone. Taken altogether, we suggest that the HR cell death is separated from the resistance mechanisms which lead to PVY restriction in Ny-1 genetic background. We propose that HR should be regarded as a process where the dynamics of events is crucial for effectiveness of viral arrest albeit the exact mechanism conferring this resistance remains unknown.

Surveillance of human enteric viruses in coastal waters using concentration with methacrylate monolithic supports prior to detection by RT-qPCR.

This is the first surveillance study using methacrylate monolithic supports to concentrate environmental coastal water samples, prior to molecular target detection by RT-qPCR. Rotaviruses (RoV) and Noroviruses (NoV) were monitored in a polluted area at the Bay of Koper (Gulf of Trieste, Northern Adriatic Sea) and at a nearby bathing area and mussel farm areas. RoV and NoV are released into the Bay of Koper, with higher rates close to the discharge of the wastewater treatment plant, however, they can be detected at recreational and mussel farming areas. Our results showed that water bodies considered safe based on FC concentrations, can still have low, yet potentially infective, concentrations of human viruses.